CN107831285A

CN107831285A - A kind of dystrophication monitoring system and its method based on Internet of Things

Info

Publication number: CN107831285A
Application number: CN201710043749.8A
Authority: CN
Inventors: 丁玉平
Original assignee: Jiangsu Jinwei Surveying And Mapping Service Center
Current assignee: Jiangsu Jinwei Surveying And Mapping Co ltd
Priority date: 2017-01-19
Filing date: 2017-01-19
Publication date: 2018-03-23
Anticipated expiration: 2037-01-19
Also published as: CN107831285B

Abstract

A kind of dystrophication monitoring system and its method based on Internet of Things, including parameter collection module, GPRS transmission module, base station, GPS, satellite, the communication server, Surveillance center, it is characterized in that：The acquisition module is used for the water quality parameter for gathering monitoring waters；The GPRS transmission module is linked by RS485 and acquisition module；The satellite sends the geographical position of acquisition module in monitoring basin to GPS；The GPS is uploaded to base station by GPRS transmission module；Gathered data is transferred to the communication server by the base station by wireless network, the data received in Surveillance center's real-time calling communication server, the Surveillance center includes being based on Distribution GIS functional module, the Distribution GIS functional module uses client/server (C/S) pattern, has the characteristics of Monitoring Data renewal speed is fast；The Distribution GIS functional module realizes efficient storage and the management of monitored area geo-spatial data using Oracle+ArcSDE frameworks.

Description

River and lake pollution monitoring system and method based on Internet of things

Technical Field

The invention relates to an environment monitoring system, in particular to a river and lake pollution monitoring system and method based on the Internet of things.

Background

The water environment capacity is utilized as a natural resource for a long time without compensation in the process of rapid development of the economic society. As the degree of development and utilization thereof increases, scarcity becomes more and more prominent, and therefore, research on the value of environmental capacity is very necessary. The water environment capacity is a basic basis of environment target management, is a main constraint condition for regional environment planning, and is also a key technical support for controlling the total amount of water pollutants. The calculation of the water pollutant capacity and the implementation of total amount control are the most important components of the basic technical work of water environment management, and are also important measures for guaranteeing the safety of the water environment of the drainage basin and promoting the sustainable development of the economy and the society of the drainage basin. Therefore, research on water environment capacity calculation and capacity gross control has become one of the leading fields and hotspots of water environment management science.

In the prior art, an application of GIS spatial analysis in water pollution monitoring is disclosed (geospatial information, volume 3 of 6.2004, vol. 3, shouli, etc., pages 32-33), which simply introduces the workflow of a river basin water pollution prevention planning GIS system, and an important problem solved when the GIS system adopting a large number of mathematical models is used for spatial analysis is how to fully utilize the mathematical models to serve a spatial analysis task, and the combination of the mathematical models and the spatial analysis task comprises the following modes: 1. loose bonding: the mathematical model system and the GIS space analysis system operate independently and respectively operate in independent systems, and data communication between the mathematical model system and the GIS space analysis system is carried out through ASCII files or binary systems. The user is responsible for formatting the file according to the format determined by the GIS! This combination is performed on the same computer or on different computers of the local area network in an online manner; 2. tight coupling: in this case, the data model is still different, but the automatic exchange of data between GIS and spatial analysis is performed through a standard interface without user intervention. This improves the efficiency of data exchange, but requires more programming tasks, requiring the user to be responsible for the integration of the data; 3. complete integration: from the user's perspective, this integration is to perform the related operations under the same system. Data exchange is based on the same data model and database management system. The interaction between the mathematical model and the spatial analysis is very efficient.

Chinese patent application (application number: CN201310116788) discloses a method for calculating the environmental capacity of a small watershed under the support of GIS technology, which determines the water area range of a control unit; determining a land area catchment range of the control unit by using a method of combining a hydrological analysis module in ArcGIS software and actual river data of GPS positioning correction to obtain a control unit with water-land response; evaluating the water quality condition; the statistical data of the pollution source is utilized, the actual investigation result of the pollution source is combined, and the river inflow amount of the point source and non-point source pollutants is counted according to the control unit; reversely deducing the flow of each control section on the water flow balance device according to the water flow balance; the water quality model parameter calibration, verification and application deducts the river inflow amount of non-point source pollutants of each control unit to obtain the available water environment capacity.

However, the prior art does not provide an effective system and method, and how to monitor and treat water pollution in real time still leaves the front of decision makers.

Disclosure of Invention

The invention provides a river and lake pollution monitoring system and method based on the Internet of things, and aims to overcome the defects in the prior art.

The invention is realized by the following technical scheme: including parameter acquisition module, GPRS transmission module, basic station, GPS receiver, satellite, communication server, surveillance center, characterized in that: the acquisition module is used for acquiring water quality parameters of a monitored water area; the GPRS transmission module is linked with the acquisition module through RS 485; the satellite sends the geographic position of the acquisition module in the monitoring flow domain to the GPS receiver; the GPS receiver is uploaded to a base station through a GPRS transmission module; the base station transmits the acquired data to the communication server through a wireless network, the monitoring center calls the data received in the communication server in real time, the monitoring center comprises a GIS function module based on a geographic information system, the GIS function module based on the geographic information system comprises a GIS function module based on the geographic information system, and the GIS function module adopts a client/server (C/S) mode, so that the monitoring data updating speed is high; the GIS functional module of the geographic information system realizes efficient storage and management of basic geographic data of a monitoring area by adopting an Oracle + ArcSDE framework.

Preferably, the sensor nodes in the acquisition module adopt a star networking structure, the upper level of the acquisition module is a transfer node, a transfer node is arranged in a region with a radius of one hundred meters, and monitoring data of other sensor nodes are uploaded to the transfer node.

Preferably: each sensor node in the parameter acquisition module comprises a sensor probe, a signal acquisition unit, a signal conditioning unit, a signal correction unit, a processor unit, a memory, an energy supply unit and a wireless communication unit; the sensor probe realizes the sensing of the water body and acquires parameters in the water body according to the requirement; the signal conditioning unit, the signal acquisition unit and the signal correction unit have the functions of acquiring, processing and filtering data acquired by the sensor probe; the processor unit realizes the functions of task scheduling and equipment control; the wireless communication unit is mainly used for receiving and transmitting data; the storage space of the sensor unit is small, and the sensor unit is used for storing temporary data; the energy supply module is used for providing required electric energy for each part of the node.

Preferably: when the system receives new CPS positioning data information, judging whether the CPS positioning data information is associated with the last estimated data or not, and if the CPS positioning data information is associated with the last estimated data, updating the track by the new GPS data information; if not, the information point is the starting point of the new flight path; the position of the next GPS data point is then estimated based on the new course point and the mathematical model calculation, that is: setting an associated mathematical model as a circle with the radius of 10 meters, namely new CPS data information needs to be in the circle with the previous point as the center of the circle and the radius of 10 meters, if the CPS data information is in the circle, tracking filtering is carried out, otherwise, tracking divergence is carried out, in addition, in fixed point positioning filtering, if the CPS data information is judged to be tracking divergence, the new CPS data information is not immediately taken as the starting point of a new track, but the point is filtered, estimation association is carried out again by using the previous track point, and if the CPS data information for the third time is tracking divergence for three times, the CPS data information for the third time is taken as the starting point of the new track; the track information may be displayed on an electronic map.

Preferably: the GIS function module of the geographic information system is combined with a neural network, the data storage function of the GIS is utilized, factors participating in evaluation are selected and determined according to the factors in the neural network model, and then the factors are input into the GIS system in the form of map layers, and the relation analysis of data is facilitated by utilizing the space analysis capability of the GIS; in addition, some of the obtained factor map layers are of a continuously distributed type, and therefore, the continuously distributed factors also need to be reclassified; when the system is implemented, index values of various factors in the primitive region can be written into the middle database for the direct calling of the artificial neural network evaluation model; the GIS functional module has powerful graphic display and output processing functions, and the analysis and prediction results can be directly mapped through the GIS by writing the results obtained by the evaluation model into the attribute data of corresponding primitives, and danger grade areas are divided by colors.

The invention also discloses a monitoring method of the river and lake pollution monitoring system based on the Internet of things.

Has the advantages that: by adopting the technical scheme, the invention realizes the real-time monitoring of the pollution of rivers and lakes and provides a reliable basis for the leading layer to treat the water pollution early.

Drawings

Fig. 1 is a general structure diagram of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 2 is a sensor node structure diagram in a parameter acquisition module of the river and lake pollution monitoring system and method based on the internet of things.

FIG. 3 is a schematic diagram of wind-solar hybrid power generation of the river and lake pollution monitoring system and method based on the Internet of things.

Fig. 4 is a schematic diagram of connection between a buoy and a monitoring system through a GPRS in the river and lake pollution monitoring system and method based on the internet of things.

Fig. 5 is a flow chart of GPRS data link of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 6 is a GPS positioning data processing flow chart of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 7 is a transfer node structure diagram of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 8 is a schematic diagram of a communication networking mode of 'sensor nodes-transit nodes' of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 9 is a schematic view of a Modbus communication mode of a monitoring center and a water quality multi-parameter acquisition module of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 10 is a GPRS Modbus communication flow chart of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 11 is a schematic view of a water quality environment monitoring information management platform of the river and lake pollution monitoring system and method based on the internet of things.

Fig. 12 is a network topology schematic diagram of the river and lake pollution monitoring system and method based on the internet of things.

Detailed Description

The river and lake pollution monitoring system based on the Internet of things comprises three layers: firstly, a perception layer is used for realizing perception quantification of various ecological environment parameters by adopting various sensors; and the network layer is used for realizing data transmission from the sensing layer to the application layer. And finally, the application layer obtains a relevant conclusion through data integration and analysis to support management decision, and simultaneously remotely controls the working state of the sensing layer at the next time according to needs.

1. Sensor node design of sensing layer

The sensing layer at the bottommost layer of the system consists of various sensor nodes arranged in monitored rivers and lake waters to form a parameter acquisition module. The design target of the sensor node is mainly miniaturization, low power consumption and low cost, so that the large-scale arrangement of the nodes is facilitated.

The bottommost layer is a buoy type sensor node which has the functions of monitoring various indexes of the water body and uploading data through a wireless local area network. The sensor nodes in the acquisition module adopt a star networking structure, the upper level of the acquisition module is a transfer node, a transfer node is arranged in a region with a radius of one hundred meters, and monitoring data of other sensor nodes can be uploaded to the transfer node. The transfer node has the function of carrying out wireless communication with the monitoring control center, and can upload the collected monitoring data of the area to the monitoring control center. The monitoring control center can perform operations such as real-time online receiving, processing and storing on the monitoring data. The monitoring control center can send a monitoring command of the next time to the transfer node, and the transfer node distributes the command to the sensor nodes in the area under the control of the transfer node. The loop operation process can realize remote monitoring of the river and lake water bodies.

Fig. 2 is a schematic diagram of a sensor node. Each sensor node in the parameter acquisition module mainly comprises a sensor probe, a signal acquisition unit, a signal conditioning unit, a signal correction unit, a processor unit, a memory, an energy supply unit, a wireless communication unit and the like. The sensor probe realizes the sensing of the water body and collects parameters in the water body according to the requirement. The signal conditioning unit, the signal acquisition unit and the signal correction unit have the functions of acquiring, processing, filtering and the like on data acquired by the sensor probe. The processor unit realizes the functions of task scheduling and equipment control. The wireless communication unit is mainly used for receiving and transmitting data. The storage space of the sensor unit is small, and the sensor unit is used for storing temporary data. The energy supply module is used for providing required electric energy for each part of the node. The processor is preferably an ARM series, and functional programs can be freely written or operated according to design requirements; after the sensor probe collects data, the sensor probe transmits the signals to a processor unit after signal amplification, isolation, filtering and A/D conversion, the amplifier is preferably an OP27 chip, the isolation function adopts photoelectric isolation, an optical coupler of the amplifier adopts 6N136 of the Fairchild Semiconductor company, and filtering adopts a second-order passive filter; the a/D converter is preferably a 16-bit analog/digital converter.

The sensor probe is placed in a water body to be detected for monitoring, a detected object is identified and converted into an electric signal through the chemical probe, the electric signal is amplified and processed through the conditioning circuit, and accurate data are obtained through signal acquisition and correction processing.

Because in different rivers and lakes, the water body index that different nodes need to detect is different, therefore for the commonality of system, sensor probe adopts the modularized design in this application, promptly: (1) a unified hardware interface is defined between the different types of sensor probes and the processor unit. (2) A unified communication protocol is defined between the different types of sensor probes and the processor unit.

In the design of the sensing layer, different sensor probes are required to be configured for different monitoring indexes, such as the heavy metal monitoring indexes of PH value, temperature, nitrite nitrogen, petroleum, dissolved oxygen, arsenic, mercury, cadmium and the like, are selected as research objects, and in the engineering design, the sensor probes are flexibly increased and decreased according to the monitoring indexes.

The sensor nodes described above are typically placed on a buoy platform, the structure of which is described in more detail below.

The buoy platform is used for providing a platform and protection for installation of the whole buoy system, and is used for placing monitoring instruments, sensor instruments, communication modules and a power supply system. The platform mainly comprises a buoy, a protective fence, a navigation mark lamp, an anchor system, an instrument mounting hole, an equipment box and the like. The buoy is used for building a buoy platform, the size of the buoy platform can be customized according to needs, the buoy platform is made of corrosion-resistant, anti-freezing, anti-oxidation and anti-ultraviolet reinforced materials, and is not corroded by seawater, chemicals, medicaments, oil stains and aquatic organisms; guard rails are arranged on the periphery of the buoy platform, and the safety protection effect is achieved on operation and maintenance personnel and equipment on the platform. The protective guard is made of stainless steel 304, has strong corrosion resistance and can be suitable for the long-term outdoor working environment. A navigation mark lamp is arranged at the top of the buoy platform equipment box and emits flickering light at night or cloudy days; the buoy is fixed in a designated installation water area through an anchor system, and the anchor system comprises an anchor, an anchor chain and a floating ball; the equipment box is made of stainless steel materials, is firmly connected with the buoy platform, is provided with solar cell panels on four sides, is a sealed waterproof equipment cabin, and is used for installing equipment such as a power supply system and data acquisition and transmission. The wind-solar combined power supply system consists of a solar cell panel, a vertical axis wind driven generator, a plurality of blocks of 120AH colloid storage batteries and a wind-solar complementary controller.

Because each buoy platform is an independent system, the power supply system of the buoy platform is particularly important, and if the power supply system can not supply power normally, the water area monitoring node can not operate normally, the invention further introduces a wind-solar combined power supply system, and because most of the buoy platforms are far away from a national power grid, each buoy platform power supply system adopts off-grid wind-solar complementary power generation, which is shown in the attached figure 3.

The off-grid wind-solar hybrid power generation system comprises a wind driven generator, a photovoltaic module, a controller, a storage battery pack, an inverter, a load discharger and the like. The power generation part comprises 1 wind driven generator and a solar photovoltaic module, a storage battery is charged through a controller and is converted into alternating current through an inverter to supply a load, and the load is an alternating current component required by a worker when detecting and maintaining the buoy platform, such as alternating current loads of an oscilloscope, a welding gun and the like; in order to better absorb sunlight, a solar energy absorption device is added on the solar cell panel, so that the sunlight is more effectively absorbed; the load release device is used for releasing electric energy led down by the lightning arrester; the controller adjusts the storage battery in real time according to the continuous change of light intensity, wind intensity, load and the like, and the continuous and stable work of the load is ensured. Important components of the controller system have protection functions of preventing the storage battery from being overcharged and overdischarged.

The main part of the wind-solar power generation system is designed according to the water area position of the buoy platform.

Accumulator part

The battery capacity will be selected according to the following equation.

In the formula, C is the capacity of the storage battery pack Ah, P is the total power of the wind-solar hybrid system W, t is the maximum discharge time h, U is the discharge voltage V, η f is the discharge depth of the storage battery, and phi is the allowance error of the storage battery.

Power of the wind power generator:

in the formula, P1 is the power of the wind driven generator, W; p is the total power of the wind-solar hybrid system, W; t is the maximum discharge time, h; t1 is the windy time, h; t2 is the maximum continuous time of wind, d, for which solar energy cannot generate electricity.

Photovoltaic power generation part

The total number of the solar cell modules in series connection is as follows:

NS＝Vf+Vi/Vm，

in the formula, Ns is the total number of the solar cell modules in series connection; vf is the floating charge working voltage, V, of the storage battery; vi is the series loop line voltage drop, V; vm is the photovoltaic module peak voltage, V.

Inverter with a voltage regulator

The performance characteristics of the inverter are controlled by an ARM chip, sine waves are output, and the inverter has protection functions of circuit breaking, overcurrent, overvoltage, overheating and the like, and the capacity of the inverter is as follows:

in the formula, PN is the capacity of the inverter, VA, P is rated output power, W, N is the power consumption rate, M is the load unbalance coefficient of each phase, S is the load power factor, and η N is the efficiency of the inverter.

Through the above description, the storage batteries are 6 120AH colloid storage batteries, 200W vertical axis wind driven generators and 4 100W solar panels; the inverter is a 100W integrated chip inverter, and the specific model is determined according to the design requirement.

The solar panel absorbs solar energy in all directions, converts the solar energy into electric energy and sends the electric energy to the storage battery for storage, and the storage battery is positioned in the waterproof storage battery bin; the vertical axis wind driven generator converts wind power into electric energy, and the electric energy is transmitted to the storage battery for storage and is used for normal operation of the system; the wind-solar complementary controller is used for controlling the work of the power supply system, plays a role in overcharge protection on the electric energy storage battery and effectively prolongs the service life of the battery.

Design of data acquisition, conditioning and correction functional module

The data acquisition module adopts a modular design; multi-channel data acquisition and recording, and has the functions of data processing, programming and alarming; data is not lost when power is off; the communication interface is RS232 or RS 485.

Data conditioning and correction mode:

assuming that the monitored object is a river or a lake, hundreds of buoy platforms are launched, and the monitoring ranges of the nodes of the data acquisition modules on the plurality of buoy platforms form a huge monitoring area, however, due to the limitations of the monitoring ranges and the reliability of the sensor nodes, when the nodes are deployed, the monitoring ranges of the sensor nodes need to be overlapped, so that the robustness and the accuracy of information obtained by the whole network system are improved. Therefore, data acquired by the sensor nodes are redundant inevitably, and therefore in a path that the monitoring data are transferred to a sink node (or a base station) for collecting the data through a multi-hop route by the nodes, the data need to be fused to reduce redundant information, improve the quality of transmitted data and reduce the energy consumption of the nodes.

The invention adopts a clustering fusion algorithm of large-scale data collection, and better fuses the data of the monitoring area through the cooperation of each cluster head node and member nodes in the cluster. The algorithm is realized based on a generation technology of a 'virtual node', namely, a distribution state of monitoring data in a cluster or in a certain range is represented by a polynomial fitting coefficient, data transmitted between cluster head nodes or between the cluster head nodes and a target node (a base station or an actuator node) is the polynomial fitting coefficient reflecting the monitoring data state in the certain range, and when the cluster head nodes or the base station perform data reproduction or data online fusion, data acquisition nodes reflecting the data state of an original monitoring area and monitoring values thereof are generated in a memory again according to the obtained fitting coefficient. These data collection nodes are referred to as "virtual nodes" because they exist only in memory and not actually.

Fitting of 1 cluster interior polynomial

For a cluster-type data acquisition network, the data acquired by the nodes in the cluster are often relatively large in correlation, and for a cluster containing N nodes, the numerical value acquired by the sensor nodes Si (xi, yi) in the cluster is assumed to be

i ═ l,2 … N, f (xi, yi) is a binary polynomial that can satisfy the error requirement, expressed as:

f(x_i，y_i)＝X_iAY_i

wherein:

X＝[1，x，x²，...，x^m-1]

Y＝[1，y，y²，...，y^n-1]^T

generally, N is more than mn, in order to obtain the system matrix A, the monitoring values of all the nodes in the family are used, the minimum two-component method is adopted,

order:

wherein:

g_jk＝x^j-1y^k-1，j＝1，2，...，m，k＝1，2，...，n，

order:

wherein,andrespectively representing row vectors formed by straightening the matrix G and the matrix A according to rows, wherein n is a natural number. In an ideal state, the water-soluble polymer is,

the deformation is as follows:

this then gives:

Z＝Oθ

whereinQ＝[q₁，q₂，...，q_N]^T

Then:

θ＝(Q^TQ)^-1Q^TZ

setting of error level:

due to the fact that the network scale is large, the phenomenon that data acquired by sensor nodes in one area are very close to the true value and the error of monitoring values in one area is large can occur, and the mean square error is still metTo eliminate this, the invention redefines ξ valid errors, i.e. small errors ξ, which are unavoidable due to various reasons, for ξ, it is agreed that ξ is mainly related to the average error epsilon of the monitored data and the maximum error lambda preset by the system, wherein,

is obviously present

Dividing lambda into k equal parts

Mean error of

The effective error is defined as:

order toFor all possible values of (m, n), if e_iN, indicating that the error of the node value is greater than the valid error, and recording the node and the monitored value of the node,

order tol represents the number of node values larger than the effective error, andthen (m)₁，n₁) I.e. the power of the polynomial coefficient sought.

2. Design of network layer transfer node

See figure transit point structure diagram 7. The network layer in the system has the functions of being responsible for by the transit node, and the main functions are as follows: (1) the monitoring and control center is responsible for data transfer between the sensor nodes and the application layer monitoring and control center, receives a control command from the monitoring and control center, starts the sensor nodes to carry out data acquisition, then collects the measurement data of the sensor nodes in the subordinate area, stores the measurement data into the memory, and packs and sends the data to the monitoring and control center after the data acquisition is finished. (2) And as a gateway, the wireless sensor network is connected with the mobile communication network.

The network layer transfer node is mainly characterized in that a wireless communication unit comprising a sensor node-transfer node is added on a sensor node and is linked with a processor unit.

See fig. 8 for an illustration. The sensor node-transit node wireless communication unit is responsible for data transmission between the sensor node and the transit node, and has an ad hoc network function, a network topology structure is diverse, large-area water bodies in rivers and lakes can be covered, the cost is low, and the sensor node-transit node wireless communication unit is suitable for arrangement of a plurality of nodes. The network topology structure of the wireless communication unit is mainly divided into three types, namely star type, mesh type and cluster type. The invention preferably adopts a star networking mode for wireless communication between the sensor node and the transfer node and between the transfer node and the monitoring control center.

Design of data transmission module

And various communication modes such as GSM, GPRS/CDMA, 3G, 4G networks, satellite communication and the like can be selected, and data transmission and remote control are realized. The data communication module can adopt SMS short message transmission to directly send short messages to a related server and a monitoring center, and the data transmission module has the function of carrying out SMS alarm to multiple points. The data transmission adopts a binary encryption protocol, and the data security is ensured. The data transmission can be forwarded to a plurality of monitoring centers through server relay. And the data transmission module automatically restarts at regular time to ensure that the connection is not dropped for a long time.

See fig. 4 for an illustration. The buoy platform logs in the Ethernet through GPRS/CDMA and sends data to a designated network server through HTTP/FTP. The server automatically parses the encrypted data and imports the data into a database. Meanwhile, once alarm information exists, the short message can be directly sent to a specified mobile phone, so that the GPRS is combined with the short message to ensure that data is not lost.

GPRS wireless communication module design

The GPRS wireless communication module adopts packet switching technology, and compared with the circuit switching mode of telephone service, the GPRS wireless communication module only occupies channel resources when data is transmitted, has high channel utilization rate, and allows a plurality of users to share certain fixed channel resources. The GPRS is particularly suitable for intermittent, burst or frequent small-amount data transmission and occasional large-amount data transmission, and has the obvious advantages of real-time online, quick login, high-speed transmission and free switching. The most important feature of GPRS technology is that the user can remain always on. The mobile terminal can realize GPRS wireless communication only by inputting an account number to establish connection. The GPRS communication is operated in the specific process that after a user logs in a WAP website, radio frequency parameters are initialized, and as long as any hypertext link is clicked, a terminal can receive and transmit packet data through a wireless channel transceiver. If the webpage is not operated for a long time, the terminal can be switched into a quasi-dormant state. In this case, the terminal does not immediately disconnect all links, but only releases the channel it occupies to other users for data transmission. The method still keeps logical connection with the GPRS network, when a user presses the link again, the terminal immediately sends a command to apply for a wireless channel, unlike the common dial-up networking, the working process that the GPRS can be networked only by dialing up again after disconnection is module initialization, an internal protocol stack is set, APN nodes are visited, whether PPP is connected or not is checked, if the PPP is connected successfully, TCP connection is established, then the link state is inquired, the available buffer size is checked, if the buffer is large enough, data transmission is carried out, and the link TCP state is closed and the frame is finished after the data transmission is successful. The GPRS link flow diagram is shown in figure 5.

The invention adopts a GPRS module with the type of SIM300, which is a three-band GSM/GPRS module, comprising 3 frequencies: EGSM900MHZ, DCS1800MHZ, PCS1900MHZ, and the SIM300 provides GPRS channels of type 10.

GPS module data processing

The GPS module belongs to the prior art, however, in the present invention, the positioning signal received by the GPS module is subjected to data processing by an engineer. The specific treatment method is as follows: when the system receives new CPS positioning data information, judging whether the data is associated with the last estimated data, if so, updating the track (tracking filtering) by the new GPS data information; if not, the information point is the starting point of the new flight path (tracking divergence). Then, estimating the position of the next GPS data point according to the new track point and a related mathematical model, for example, setting the related mathematical model as a circle with the radius of 10 meters, namely, the new CPS data information needs to be in the circle with the radius of 10 meters and the previous point as the center of the circle, if the CPS data information is in the circle, tracking filtering is carried out, otherwise, tracking divergence is carried out, in addition, in fixed point positioning filtering, if the CPS data information is judged to be tracking divergence, the new CPS data information is not immediately taken as the starting point of the new track, but the point is filtered, the previous track point is used for estimating correlation, and if the CPS data information for the third time is continuously carried out for three times and is taken as the starting point of the new track; the track information may be displayed on an electronic map. The above GPS positioning data processing flow is shown in fig. 6.

Design of transmission protocol between data

MODBUS communication protocol, which enables the controllers to communicate with each other, with the controllers communicating with other devices via a network (e.g., GPRS/CDMA). The controller communication uses a master-slave technique, i.e. only one device (master) can initiate a transmission (inquiry), and the other devices (slaves) react accordingly based on the data provided by the master inquiry. Modbus can theoretically connect (address) a master station and a plurality of slave stations. The Modbus completes communication in an asynchronous serial port mode, and the physical interface adopts an RS-485 or RS-232 mode. The Modbus has two communication modes, namely a response mode and a broadcast mode. The response mode is that the master station sends a command (the address of the slave station cannot be '0') to a certain slave station, then waits for the response of the slave station, and after receiving the command sent by the master station, the slave station executes the corresponding command, returns the execution result to the master station as a response, and then waits for the next command of the master station. In the broadcast mode, the master station transmits a command (slave station address is 0) to all the slave stations without waiting for the slave stations to respond, and the slave stations execute the command and do not respond to the master station after receiving the broadcast command. The Modbus communication protocol has two transmission modes, ASCII (american standard code for information interchange) mode and RTU (remote terminal unit) mode. Using ASCII mode, the message starts with a ": character and ends with a carriage return linefeed. Using the RTU mode, message transmission begins at least with a pause interval of 3.5 character times, thus a multiplicity of character times at the network baud rate, as shown below in table 1 as T1-T2-T3-T4). The first field of transfer is the device address. The transmission characters that may be used are hexadecimal 0.. 9, a.. F. The network device continuously detects the network bus, including during the stall interval. When received by the first domain (address domain), each device decodes to determine whether it is destined for itself. A new message can only occur after a pause of at least 3.5 character times after the last transmitted character. The entire message must be sent continuously. If a quiet time greater than 1.5 characters occurs during the transmission of the frame information, the receiving device refreshes the incomplete information and assumes the next address data. A new message sent immediately after the same message (without 3.5 characters of quiet time) will generate an error. This is because the CRC check code of the combined information is invalid and causes an error. A typical message frame is shown in table 1:

start bit	Device address	Function code	Data of	CRC checking	Ending symbol
						T1-T2-T3-T4	8Bit	8Bit	n 8 bits	16Bit	T1-T2-T3-T4

The pause of the Modbus RTU is divided into a command frame (inquiry frame) and a response frame in response mode. The command frame is a general format command frame, the response frame has a difference between an explicit length frame and an implicit length frame, the format of the command frame is given in table 2, the format of the explicit length response frame is given in table 3, and the format of the implicit length response frame is given in table 4.

TABLE 2

TABLE 3

Slave station address

Function code

Data length

Data of

Checksum

TABLE 4

Slave station address

Function code

Data of

Checksum

The buoy platform carrying the water quality multi-parameter data acquisition module serves as a slave station, the master station takes the monitoring center as a core, the master station and the slave station realize the sending and receiving of instruction data through a Modbus communication protocol, and the adopted communication mode is a response mode, as shown in Table 5.

The water quality multi-parameter acquisition module supports a standard Modbus RTU protocol, and developers such as the address, baud rate, character parity check, stop bit number and the like of the water quality multi-parameter acquisition module can define and set the water quality multi-parameter acquisition module by themselves. The water quality multi-parameter acquisition module supports a function code '04' to read acquisition parameter values of all channels of the current acquisition module, and a command frame responded by the acquisition module adopts a display length response frame. Assuming that the address of the water quality multi-parameter acquisition module is 1, the complete Modbus command frame format for reading the 1 st channel parameter acquisition data of the water quality multi-parameter acquisition module is shown in table 5, and the Modbus communication mode of the water quality multi-parameter acquisition module is shown in fig. 9.

TABLE 5

Design of serial port communication protocol

The data transmission of the system adopts serial communication, the application of the serial communication technology is wide, and the serial communication is often adopted to exchange data and information in data communication, computer networks and distributed control systems. This design adopts multichannel RS485 serial ports for communicate with the treater, can convey the information transmission of treater to acquisition terminal, also can realize two-way communication with acquisition terminal's information feedback to central processing unit. The system adopts a SerialPort control provided by Visual Studio 2010 to realize serial port communication, and the SerialPort control and other controls of C # interact with users through a series of methods, attributes and events. Data can be sent and received as long as the properties, methods, events of the SerialPort control are designed.

The water quality parameter acquisition and processing program transmitted by the GPRS wireless network mainly comprises the following parts, as shown in the attached figure 10:

(1) initializing a communication program, wherein the initialization data comprises the address of communication equipment, the communication rate, a parity check mode, communication overtime waiting time and the like;

(2) the data reading module is used for reading the data of the memory unit, and sending a data reading request to the data acquisition module by setting the initial address of the read data, the byte number of the read data, the functional code of the read data and the like;

(3) and (4) data acquisition alarm processing, namely executing a corresponding alarm processing program when the acquired data parameters exceed a set threshold value.

After the program runs, firstly setting the parameters of the serial port, and setting the parameters of the serial port of the system as follows:

serial port number COM3

Baud rate of 9600bps

8 bits of data

Stop position 1

Check bit-no check bit

And opening the serial port, setting the equipment address, the function code, the initial address and the number of registers, and sending. The module responds accordingly by sending a data command to be queried. The query module type register command, 3504(HEX), is sent.

3. Application layer, namely water quality monitoring information management platform (monitoring center)

The water quality monitoring information management platform is a system which is based on a geographic information system and integrates functions of remote automatic monitoring data acquisition, data summarization, analysis, remote control and the like, and can realize data transmission and data sharing of the water quality multi-parameter acquisition module and the platform. The dynamic active uploading of real-time data, minute data and state data of substation operation can be realized, and the functions of data display and release and water quality data analysis and early warning are realized.

Logic architecture of water quality monitoring information management platform

The geographic information service system provides a service support platform for service analysis and application of terminal users for water quality analysis service, data monitoring service and data communication service in real time. The application subsystems such as real-time monitoring data display, water quality data analysis, mobile terminal access, short message notification alarm and site operation monitoring provide all-around monitoring and analysis of various pollution sources in estuaries and sea areas for users. A detailed system logic architecture diagram is shown in fig. 11.

The platform design is closely combined with the user service characteristics and fully applies the latest technology of the current computer. The application of the geographic information service platform brings the best convenience and friendly experience to users, and fully embodies the human-oriented design concept of the system. Service-oriented design and interface design improve the expandability of the system, such as:

and (3) field monitoring point expansion: the platform can be used for newly adding more various monitoring points including pollution sources at any time, and the expansion of the monitoring points is completed after the monitoring points are registered and corresponding communication parameters are set.

And (3) communication mode expansion: the system can adapt to various communication transmission modes, only corresponding communication modules need to be added for new communication means, and the main body of the platform does not need to be changed.

Network topology

The network topology of the present platform is schematically illustrated in fig. 12.

The water quality monitoring information management platform consists of a Web application server, a database server, a real-time analysis server, a communication server and a substation data acquisition instrument. The communication server is responsible for data communication with the water quality monitoring substation, and the equipment provided by the communication server meets various communication modes, such as optical fiber broadband, GPRS/CDMA, PSTN, GSM, ADSL/ISDN and the like. The configuration of the communication server and its performance should be sufficient to meet the current system communication needs and future system expansion needs. The communication Server stores the received data of the remote substation in an SQL Server/Oracle database.

The central server deployment is a typical and recommended mode, and under the condition that the number of terminal access and monitoring sites is small, the number of central hardware servers can be reduced, and the following merging deployment mode is adopted. After the combined deployment is adopted according to actual conditions, the use requirements can be met, and the construction cost can be greatly reduced.

When entering the water quality monitoring information management platform system, a user needs to perform identity verification, so that the user can use the operation corresponding to the identity of the user.

Users with different rights enjoy different access rights to the platform. Besides, the system also ensures the safe operation of the platform through the following ways and means.

(1) The data transmission safety can adopt VPN to strengthen the precaution capacity in the data transmission process, and the safety of remote data acquisition and transmission is improved.

(2) Data storage security

And a storage device with large capacity and high I/O throughput capacity is adopted to ensure the safety and reliability of data storage. The substation can automatically store the data after power failure, has the capacity of storing original data for more than half a year, has the function of automatic backup of the data of the central station, and can be manually restored when a database has a catastrophic failure.

(3) Monitoring site security

When a relevant monitoring instrument for a station room is arranged in the fixed station, the platform can give an alarm in time for potential safety hazards such as acid leakage, alkali leakage and the like of the fixed station.

The monitoring center functions are further described:

design based on Geographic Information System (GIS) functional module

Geographic Information System (GIS) is a new discipline integrating multiple disciplines such as computer discipline, informatics, geography and the like, and is composed of a computer system, geographic data and users. The method organically combines the geographic position and the related attribute, and accurately and truly produces and outputs the geographic information in a graph-text manner according to the actual requirement through the operations of acquisition (integration), storage, retrieval, analysis and the like of geographic data with spatial connotation. At present, the application and development of GIS in various industries become an inaudible international trend.

ArcSDE is a member of the ArcGIS family developed by the national institute of Environmental Systems (ESRI), a spatial database middleware technology. The ArcSDE is a GIS channel between an ArcGIS functional module and a relational database (the background relational database of the system adopts Oracle), the ArcSDE takes the database as a background storage center to provide rapid space data access for front-end GIS application, and the safety and high efficiency of rapid reading of mass data and data storage are important characteristics of the ArcSDE. The ArcSDE supports the ArcGIS application layer and provides DBMS channel technology so that spatial data can be stored in a variety of DBMSs. ArcSDE can guarantee all GIS functions available simultaneously without regard to the underlying DBMS. ArcSDE manages the underlying spatial data store in table form using the data types supported by the DBMS, and can access these data in the DBMS using SQL. The ArcSDE also provides open client development interfaces through which user-customized applications can also access the underlying spatial data tables.

GIS server architecture design

The system adopts a client/server (C/S) mode and has the characteristic of high monitoring data updating speed. The system firstly collects various water quality data of a monitoring area through a data collection module; secondly, the framework design adopts Oracle + ArcSDE, which is the most mature and stable spatial data management technology in the world at present and is the mainstream mode of basic geographic information database engineering construction, and the data layer of the framework adopts an Oracle database system and an ArcSDE spatial data engine to realize the efficient storage and management of the basic geographic data of the monitoring area; the middle layer realizes the access to the space data through an ArcSDE space data Engine, and constructs a space information comprehensive application development platform based on the Arc-GIS Engine and the ArcIMS technology, so as to realize the service logic of the space data application, such as the representation and operation of the space data; the application layer realizes the specific application of the basic geographic database of the monitoring area on the basis of ArcGISEngine and ArcIMS. The spatial and attribute data stored in Oracle are accessed through a spatial database engine ArcSDE of ESRI company, and the operations of water quality data inspection, warehousing and updating are carried out on the spatial and attribute data. The system completes the GIS function by embedding ArcGISEngine components of ESRI company.

Combination of GIS and neural network

The factors participating in evaluation are selected and determined according to the factors in the neural network model by utilizing the data storage function of the GIS, and then are input into the GIS system in the form of map layers, and the relation analysis of data is facilitated by utilizing the space analysis capability of the GIS. In addition, the obtained factor layer is of a continuously distributed type, and therefore, the continuously distributed factors must be reclassified. When the system is implemented, index values of various factors in the primitive region can be written into the intermediate database for the artificial neural network evaluation model to be directly called, and seamless connection of GIS data and the evaluation analysis model is really realized. The GIS has powerful graphic display and output processing functions, and analysis and prediction results can be directly mapped through the GIS by writing results obtained by the evaluation model into attribute data of corresponding primitives, and danger grade areas are divided through colors.

In order to solve the problem of collecting a small sample of data for water quality, preprocessing the data by adopting B sample least square data fitting to obtain a large sample so as to meet the requirement of input data required by a neural network model, wherein the B sample least square data fitting algorithm is as follows:

let the number of original samples be N, and each sample has a number, which is denoted as x_iNumber x of ith sample_iX is measured as i_iFalls within the interval [ a, b]In (a ═ x)₁＜x₂＜…＜xN＝b＜X_N+1＜…＜x_N+nIn constructing the ith n +1 th-order canonical B spline function with x as a variable, first, let I be x_i，x_i+1，…，x_i+n+1I is-11, …, N, as a functionThen obtainIs n +1 order difference quotient [ x ]_t，x_t+1，…，x_t+n+1](1-x)₊ ⁿ. Finally, an i +1 th order canonical B spline function for the variable is obtained: b is_t，n+1(x)＝(x_t+n+l-x_t)[x_i，X_i+l，…，x_i+l+n]×(t-x)₊ ⁿ，i＝-n，-n+1，…，N-1。

The design of the monitoring center based on a Geographic Information System (GIS) function module comprises a system menu module, a system toolbar module, a map eagle eye module, a layer management module, a thematic map making module, a layer display style setting module, a status bar information module and the like.

The system menu module realizes the following functions:

(1) and (3) GIS map operation: including zooming, roaming, site display, map area selection, and navigation of the map.

(2) Maintaining basic information of the system: the method comprises system information addition and deletion, database connection setting and the like.

(3) Data display, query and statistics: and displaying monitoring data, real-time data, hour statistical data and the like of the pollution source monitoring station as required. The monitoring data of different sites, different time periods and different projects can be obtained by inputting query and statistical conditions.

(4) Accurate positioning of an entity: pollution source point location, enterprise location and environmental protection monitoring vehicle quick positioning display etc. can carry out.

(5) And (3) data analysis: and performing visual analysis on the pollution conditions of a plurality of sites and a certain time period.

(6) And (4) report printing, namely, outputting daily reports, weekly reports, monthly reports, quarterly reports, annual reports and the like of conventional work, and also printing by self-definition.

The monitoring center realizes the functions of the monitoring data query and display subsystem.

The data query statistic function of the system comprises the steps of querying any river and lake water quality pollution monitoring station and relevant data of the station in any time period, and generating a corresponding format for a query result to display, store or print. In the data query module, the polluted project, the polluted enterprise information and the state of the monitoring instrument can be queried. The method has the advantages that the pollution item query is realized by using the CEMS (pollution analysis system) of the pollution source, information data of a plurality of monitoring sites and a plurality of items at any time period can be queried, and the query result is displayed in the form of an Excel table.

The data display module of the environmental quality monitoring system mainly comprises real-time data display and hour data display. After the system receives the water quality monitoring information data of each monitoring station, simple statistical processing is carried out, so that a user can conveniently check and master the trend of the monitoring data. A user can check and monitor real-time conditions of pollutants generated in different places of rivers and lakes in a real-time data display window according to needs. The upper part of the interface window is provided with options provided by the user, including river names, river positions, monitoring station numbers and the like

When the water pollution of the monitored area exceeds the standard, the real-time data acquisition and transmission instrument transmits information to the monitoring center server, relevant data and information are displayed on an automatic early warning page, meanwhile, an application program automatically starts an alarm signal, and the alarm signal is informed to monitoring center workers in modes of short message service, mail, QQ timely communication and the like.

The monitoring alarm system comprises a two-stage alarm system. The primary alarm system consists of an infrared detector, an audible and visual alarm, an infrared camera and a hard disk storage machine. The scanning range of the infrared detector is 120 degrees, and the infrared detector consists of 2 dual-technology outdoor detectors, so that the whole area can be covered. The secondary alarm system is formed by an infrared proximity switch and is integrated on a central station monitoring platform by an upper computer software monitoring system. When someone enters the infrared detector area, the acousto-optic alarm function and the laboratory alarm function are started, and the situation around the buoy can be checked in a monitoring room by checking information shot by the infrared camera. When someone opens the cover, the proximity switch is touched to start the secondary alarm function.

Water quality analysis

Data received by a monitoring center are mass data, the monitoring center takes longer processing time for further implementation of data processing and control measures, therefore, data mining is firstly carried out before abnormal conditions are confirmed and processed, information which is hidden in the data, unknown in advance and potentially useful is extracted from a large amount of incomplete, noisy, fuzzy and random data, clustering analysis is one of important methods for data mining, the change of marine environment parameters is gradual, even if national seawater quality standards exist, the analysis of the water quality condition not only carries out comprehensive evaluation on a plurality of indexes, but also has the characteristic of fuzzy transition, so that a membership degree concept is introduced, the analysis is more reasonable by adopting a Fuzzy C Mean (FCM) clustering method, the defect of hard classification is overcome, but the FCM based on an objective function is a local optimization algorithm, the method has the defects of sensitivity to initialization and difficulty in obtaining a global optimal solution, the clustering number of the method is selected according to experience, sufficient scientificity is lacked, and massive data clustering wastes a large amount of time and resources; a Genetic Algorithm (GA) is a random search algorithm which is developed by taking natural selection and evolution mechanisms in the biology as a reference and has self-adaptability and self-organization capability, has global search and parallel computing capability and is widely applied to solving complex optimization problems.

Therefore, the invention adopts the space vector genetic clustering analysis method to process massive data, thereby not only greatly reducing the data processing amount, but also obtaining scientific and reasonable processing results and improving the response speed of the monitoring center to abnormal conditions.

Fuzzy C-means (FCM) clustering algorithm

The FCM algorithm has good local optimization and error convergence, is a greedy algorithm, can not obtain a global optimal solution necessarily, and often falls into local optimization rather than global optimization. The algorithm comprises the following steps:

defining a finite vector x as { x }_k|x_k∈R^pAnd k is 1, 2, 3, …, n, and is classified into c types (1 < c < n), and the classification matrix U is:

U＝{u_ik|k＝1，2，3，，n；i＝1，2，3，…，c} (1)

with middle u_ikRepresenting a vector x_iBelong to class c_kDegree of membership of 0. ltoreq. u_ik≤1。

The objective function may be defined as:

wherein d is_ikIs a vector x_kTo c_iA spatial distance of c_i(1≤i≤c)，c_i∈Rp。

The algorithm is executed for a fixed iteration number before the mountain so as to avoid the condition that the termination condition cannot meet the condition of trapping into an infinite loop. The FCM algorithm is applied at Step2 in the genetic clustering algorithm Step described below.

(2) Algorithm step of genetic clustering

Step1 population initialization. The n samples are divided into c classes, each cluster center is used as a gene, a gene chain consisting of the c genes forms a chromosome, and the initial cluster centers are randomly selected, so that the initial chromosome consists of the randomly selected c genes. Setting initial values of a population size n, a maximum evolution algebra g, a cross probability Pc and a variation probability Pm. And randomly selecting n vectors from the data set S { S1, S2, … and Sm } to form an initial population, and forming a fuzzy classification matrix U.

Step2 the following operations were performed on the population:

a. randomly selecting a clustering center;

b. clustering partitioning using fuzzy C-means clustering (FCM)

c. Solving the clustering center under the current partition, wherein in order to improve the searching speed, the initial clustering center can be given according to the actual data distribution condition, and after the clustering center is obtained by obtaining the clustering partition each time, the current clustering center is used for replacing the original clustering center;

d. and calculating the fitness.

Step3 selects the operation. And selecting the next generation of individuals according to the size of the chromosome fitness by a roulette method.

Step4 crossover operation. Optionally, the two individuals are subjected to a single point crossover operation.

And Step5 mutation operation. The mutation probability is determined by a mutation probability parameter Pm, the position of the mutation is randomly generated, and the 'not' operation is carried out on the mutation position.

Step6 obtains the optimal chromosome. If the stopping condition is met, finishing the iteration and decoding a clustering center; otherwise, the process goes to Step2 and the iteration process is repeated.

In the previous description, numerous specific details were set forth in order to provide a thorough understanding of the present invention. The foregoing description is only a preferred embodiment of the invention, which can be embodied in many different forms than described herein, and therefore the invention is not limited to the specific embodiments disclosed above. And that those skilled in the art may, using the methods and techniques disclosed above, make numerous possible variations and modifications to the disclosed embodiments, or modify equivalents thereof, without departing from the scope of the claimed embodiments. Any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present invention are within the scope of the technical solution of the present invention.

Claims

1. The utility model provides a river lake pollution monitoring system based on thing networking, includes parameter acquisition module, GPRS transmission module, basic station, GPS receiver, satellite, communication server, surveillance center, characterized in that: the acquisition module is used for acquiring water quality parameters of a monitored water area; the GPRS transmission module is linked with the acquisition module through RS 485; the satellite sends the geographic position of the acquisition module in the monitoring flow domain to the GPS receiver; the GPS receiver is uploaded to a base station through a GPRS transmission module; the base station transmits the acquired data to the communication server through a wireless network, the monitoring center calls the data received in the communication server in real time, the monitoring center comprises a Geographic Information System (GIS) function module, and the GIS function module adopts a client/server (C/S) mode and has the characteristic of high monitoring data updating speed; the GIS functional module of the geographic information system realizes efficient storage and management of basic geographic data of a monitoring area by adopting an Oracle + ArcSDE framework.

2. The river and lake pollution monitoring system based on the internet of things as claimed in claim 1, wherein: the sensor nodes in the acquisition module adopt a star networking structure, the upper level of the sensor nodes is a transfer node, a transfer node is arranged in a region with a radius of one hundred meters, and monitoring data of other sensor nodes can be uploaded to the transfer node.

3. The river and lake pollution monitoring system based on the internet of things as claimed in claim 1, wherein: each sensor node in the parameter acquisition module comprises a sensor probe, a signal acquisition unit, a signal conditioning unit, a signal correction unit, a processor unit, a memory, an energy supply unit and a wireless communication unit; the sensor probe realizes the sensing of the water body and acquires parameters in the water body according to the requirement; the signal conditioning unit, the signal acquisition unit and the signal correction unit have the functions of acquiring, processing and filtering data acquired by the sensor probe; the processor unit realizes the functions of task scheduling and equipment control; the wireless communication unit is mainly used for receiving and transmitting data; the storage space of the sensor unit is small, and the sensor unit is used for storing temporary data; the energy supply module is used for providing required electric energy for each part of the node; the processor is selected from ARM8 series, and functional programs can be freely written or operated according to design requirements; after the sensor probe collects data, the sensor probe transmits the signals to a processor unit after signal amplification, isolation, filtering and A/D conversion; the amplification function adopts an OP27 operational amplifier chip; the isolation function adopts an optical coupler for photoelectric isolation, and the optical coupler adopts a 6N136 chip of Fairchild Semiconductor company (American Rapid Semiconductor); the filtering function adopts a second-order passive filter; the a/D converter is selected to be a 32-bit analog-to-digital converter.

4. The river and lake pollution monitoring system based on the internet of things as claimed in claim 1, wherein: the water quality parameters collected by the parameter collecting module comprise PH value, temperature, nitrite nitrogen, petroleum, dissolved oxygen, arsenic, mercury and cadmium.

5. The river and lake pollution monitoring system based on the internet of things as claimed in claim 1, wherein: the parameter acquisition module is arranged on the floating platform, and a power supply system of the floating platform adopts an off-grid wind-solar hybrid power generation system.

6. The river and lake pollution monitoring system based on the internet of things as claimed in claim 1, wherein: when the system receives new CPS positioning data information, judging whether the CPS positioning data information is associated with the last estimated data or not, and if the CPS positioning data information is associated with the last estimated data, updating the track by the new GPS data information; if not, the information point is the starting point of the new flight path; the position of the next GPS data point is then estimated based on the new course point and the mathematical model calculation, that is: setting an associated mathematical model as a circle with the radius of 10 meters, namely new CPS data information needs to be in the circle with the previous point as the center of the circle and the radius of 10 meters, if the CPS data information is in the circle, tracking filtering is carried out, otherwise, tracking divergence is carried out, in addition, in fixed point positioning filtering, if the CPS data information is judged to be tracking divergence, the new CPS data information is not immediately taken as the starting point of a new track, but the point is filtered, estimation association is carried out again by using the previous track point, and if the CPS data information for the third time is tracking divergence for three times, the CPS data information for the third time is taken as the starting point of the new track; the track information may be displayed on an electronic map.

7. The river and lake pollution monitoring system based on the internet of things as claimed in claim 1, wherein: the GIS function module of the geographic information system is combined with a neural network, the data storage function of the GIS is utilized, factors participating in evaluation are selected and determined according to the factors in the neural network model, and then the factors are input into the GIS system in the form of map layers, and the relation analysis of data is facilitated by utilizing the space analysis capability of the GIS; in addition, some of the obtained factor map layers are of a continuously distributed type, and therefore, the continuously distributed factors also need to be reclassified; when the system is implemented, index values of various factors in the primitive region can be written into the middle database for the direct calling of the artificial neural network evaluation model; the GIS functional module has powerful graphic display and output processing functions, and the analysis and prediction results can be directly mapped through the GIS by writing the results obtained by the evaluation model into the attribute data of corresponding primitives, and danger grade areas are divided by colors.

8. The monitoring method of the river and lake pollution monitoring system based on the Internet of things according to any one of claims 1 to 7.